BIO

ABOUT ME

I got my Bachelor of Science at College of Information Technology, Vietnam National University Hanoi in 2007. After several years working in software industry (such as FPT), I decided to pursue and finished my Master degree in Management Information System at Oklahoma State University, Stillwater, OK in 2013. Since then, I had been working as a lecturer at Thai Nguyen University, Vietnam. In 2016, I was awarded by the Vietnam International Education Development (VIED) - Ministry of Education and Training scholarship to pursue my PhD degree at Texas Tech University.

HOBBIES

INTERESTS

I usually spend my free time on fishing. I like carp and catfish.

Of course, writing is one of my favourite routines.

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RESUME

EDUCATION

2017

Now

Lubbock, TX

COMPUTER SCIENCE - PHD STUDENT

Texas Tech University

I'm currently a Phd student at the interactive data visualization lab, Computer Science Department. The Department of Computer Science engages in the research, education, and service activities required to create and disseminate the knowledge of problem solving using computers.

2011

2013

Stillwater, OK

MSIS - MASTER STUDENT

Oklahoma State University

The Master of Science in Management Information Systems Program (MS in MIS) focuses on providing solutions to business information and data needs. The core curriculum for the 34-hour program includes courses on MIS in business, database management, data warehousing, systems analysis, programming for analytics, descriptive analytics, visualization and professional development

ACADEMIC AND PROFESSIONAL POSITIONS

2008

2009

Lubbock, TX

RESEARCH ASSISTANT

Texas Tech University

The interactive Data Visualization Lab is housed at EC 305 within the Department of Computer Science at Texas Tech University. We focus on developing methods and tools for analyzing, visualizing, and interacting with massive, dynamic, and ambiguous data arised from various application domains. Our research explores the novel marriage of human-computer interaction, scientific and information visualization, computer animation, and machine learning. We move beyond traditional computing environments by experiencing interactive visualization techniques on mobile devices as well as within immersive virtual reality environments.

HONORS AND AWARDS

2017

2018

Lubbock, TX

COMPETITIVE SCHOLARSHIP

COMPETITIVE AWARD FOR ACADEMIC EXCELLENCE

The scholarship is competitive with approximately 70% of students who complete the application being awarded. TTU domestic and international degree-seeking students who will study abroad on Texas Tech approved programs, or international students seeking a degree at Texas Tech are eligible to apply. Students may apply and be awarded in more than one term. A committee of faculty and former study abroad students makes the determination of who will receive a scholarship

Project 911

COMPETITIVE AWARD FOR ACADEMIC EXCELLENCE

Project 322

COMPETITIVE AWARD FOR ACADEMIC EXCELLENCE

Scholarship No. 322 was specifically created to provide undergraduate and graduate training in the science and technology fields. The government of Vietnam committed to fully funding this initiative, which paid for all costs associated with the study-abroad experience (tuition and fees, living expenses, insurance, air and ground transport and contingencies). Additional limited support, such as language training, was provided by several scholarship host institutions/organisations

MalViz: An Interactive Visualization Tool for Tracing Malware

Vinh T. Nguyen, Akbar Siami Namin, Tommy Dang.Demonstrations

This demonstration paper introduces MalViz, a visual analytic tool for analyzing malware behavioral patterns through process monitoring events. The goals of this tool are: 1) to investigate the relationship and dependencies among processes interacted with a running malware over a certain period of time, 2) to support professional security experts in detecting and recognizing unusual signature-based patterns exhibited by a running malware, and 3) to help users identify infected system and users' libraries that the malware has reached and possibly tampered. A case study is conducted in a virtual machine environment with a sample of four malware programs. The result of the case study shows that the visualization tool offers a great support for experts in software and system analysis and digital forensics to profile and observe malicious behavior and further identify the traces of affected software artifacts.

Brno, Czech Republic

Predict Saturated Thickness using TensorBoard Visualization

Vinh T. Nguyen, Fang Jin, Tommy Dang.Workshop

Water plays a critical role in our living and manufacturing activities. The continuously growing exploitation of water over the aquifer poses a risk for over-extraction and pollution, leading to many negative effects on land irrigation. Therefore, predicting aquifer water level accurately is urgently important, which can help us prepare water demands ahead of time. In this study, we employ the Long-Short Term Memory (LSTM) model to predict the saturated thickness of an aquifer in the Southern High Plains Aquifer System in Texas, and exploit TensorBoard as a guide for model configurations. The Root Mean Squared Error of this study shows that the LSTM model can provide a good prediction capability using multiple data sources, and provides a good visualization tool to help us understand and evaluate the model configuration.

Brno, Czech Republic

ComModeler: Topic Modeling Using Community Detection

Tommy Dang, Vinh T. Nguyen.Workshop

This paper introduces ComModeler, a novel approach for topic modeling using community finding in dynamic networks. Our algorithm first extracts the terms/keywords, formulates a network of collocated terms, then refines the network based on various features (such as term/relationship frequency, sudden changes in their frequency time series, or vertex betweenness centrality) to reveal the structures/communities in dynamic social networks. These communities correspond to different hidden topics in the input text documents. Although initially motivated to analyze text documents, we soon realized the ComModeler has more general implications for other application domains. We demonstrate the ComModeler on several real-world datasets, including the IEEE VIS publications from 1990 to 2016, together with collocated phrases obtained from various political blogs.

We propose a framework and a setup for presenting complex models for curriculum contents in both augmented reality and virtual reality environment. After constructing some three-dimensional models representing real world objects such as trees, stones, rivers, dams, and buildings, our workflow uses the Unity engine in combination with Virtual Reality headset devices to create interactive applications for both Virtual Reality and Augmented Reality environments to support students understanding the curriculum contents through their surrounding. Typical challenges are addressed when creating 3D curriculum contents, integrating these models into Unity and solutions are proposed where possible. The overall structure of the project is described with some functionalities added to Unity for visualization and interaction with the models.

CancerLinker: Explorations of Cancer Study Network

Arizona, USA

CancerLinker: Explorations of Cancer Study Network

Vinh T. Nguyen, Md Yasin Kabir, Tommy Dang.Workshop

Interactive visualization tools are highly desirable to biologist and cancer researchers to explore the complex structures, detect patterns and find out the relationships among bio-molecules responsible for a cancer type. A pathway contains various bio-molecules in different layers of the cell which is responsible for specific cancer type. Researchers are highly interested in understanding the relationships among the proteins of different pathways and furthermore want to know how those proteins are interacting in different pathways for various cancer types. Biologists find it useful to merge the data of different cancer studies in a single network and see the relationships among the different proteins which can help them detect the common proteins in cancer studies and hence reveal the pattern of interactions of those proteins. We introduce the CancerLinker, a visual analytic tool that helps researchers explore cancer study interaction network. Twenty-six cancer studies are merged to explore pathway data and bio-molecules relationships that can provide the answers to some significant questions which are helpful in cancer research. The CancerLinker also helps biologists explore the critical mutated proteins in multiple cancer studies. A bubble graph is constructed to visualize common protein based on its frequency and biological assemblies. Parallel coordinates highlight patterns of patient profiles (obtained from cBioportal by WebAPI services) on different attributes for a specified cancer study.

14AUG2017

DycomDetector: Discover topics using automatic community detections in dynamic networks

DycomDetector: Discover topics using automatic community detections in dynamic networks

Tommy Dang, Vinh T. Nguyen, Md. Yasin Kabir.Workshop

Due to the rapid expansion and heterogeneity of the data, it is
a challenging task to discover the trends/patterns and relationships
in the data, especially from a corpus of texts from published
documents, news, and social media. In this paper, we introduce
DycomDetector, a novel approach for topic modeling using community
detections in dynamic networks. Our algorithm extracts
the important terms/phrases, formulates a network of collocated
terms, and then automatically refines the network on various features
(such as term/relationship frequency, sudden changes in their time series, or vertex betweenness centralities) to reveal the structure/communities in the given network. These communities are
corresponded to different hidden topics in the input texts. DycomDetector
provides an intuitive interface and supports a range
of interactive features, such as lensing or filtering, allowing users
to quickly narrow down events of interest. We also demonstrate
the applications of DycomDetector on several real world datasets to
evaluate its capabilities.

RESEARCH

TOMMY DANG

ASSISTANT PROFESSOR

Tommy Dang leads the interactive Data Visualization Lab (iDVL). He is currently an Assistant Professor in the Computer Science Department at Texas Tech University..

VUNG V. PHAM

RESEARCH ASSISTANT

He has a great interest in data analytics and data visualization and so he decided to take his PhD in Computer Science at TTU and work at the IDV Lab to strengthen his research skills and his knowledge in these fields.

VINH T. NGUYEN

RESEARCH ASSISTANT

HUYEN N. NGUYEN

RESEARCH ASSISTANT

TBA.

RESEARCH PROJECTS

Teaching Foreign Language Pronunciation through Educational Avatars.

DESCRIPTION OF THE PROJECT

Aaron Braver (Dept of English), Miranda Scolari (Dept of Psychology), and Tommy Dang (Dept of Computer Science) are investigating the effectiveness of using a computer avatar for teaching Japanese and Arabic pronunciation. We also measure learners' attention using an eye-tracker to find out the relationship between learners' attention and pronunciation development.

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TEACHING

CURRENT

NOW

2018

TEACHING ASSISTANT

TEXAS TECH UNIVERSITY

I'm a teaching assistant for the Virtual Reality course Spring 2018.

TEACHING HISTORY

2009

2010

LECTURER

THAI NGUYEN UNIVERSITY

I was a lecturer at Thai Nguyen University, Vietnam.

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SKILLS

PROGRAMMING SKIILLS

I'm experience with various programming languages.

LEVEL : INTERMEDIATEEXPERIENCE : 3 YEARS

JavaScriptC#PythonR

DESIGN SKILLS

I'm working with a variety of 2D and 3D tools.

LEVEL : INTERMEDIATEEXPERIENCE : 2 YEARS

PhotoshopIllustratorBlender3DSchetchupUnity3D

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WORKS

Reviewer

The 10th NordiCHI Conference

The 10th NordiCHI Conference

1-3 October 2018 • Oslo, Norway
Number of paper(s) reviewed: # 1.

Reviewer

The 11th IEEE Pacific Visualization Symposium

The 11th IEEE Pacific Visualization Symposium (PacificVis 2018)

April 10-13, 2018 - Kobe, Japan
Number of paper(s) reviewed: # 1

Reviewer

INT‘L SYMPOSIUM ON MIXED AND AUGMENTED REALITY

17th IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

Student Volunteers

Student Volunteers

Each year student volunteers provide essential support to the IEEE VIS Conference. The conference depends on student volunteers to staff the various conference events and special purpose conference rooms. Their enthusiastic participation enhances the conference experience for all the attendees.
Student Volunteers benefit by observing first-hand the latest advances in visualization, hearing and meeting world-class as well as next-generation visualization professionals from around the world, and building a network of research colleagues.
The Student Volunteer Program is looking for reliable, hard working and enthusiastic student volunteers to help us create a great experience and a premier conference.